At Scribd (pronounced “scribbed”), we believe reading is more important than ever. Join our cast of characters as we build the world’s largest and most fascinating digital library: giving subscribers access to a growing collection of ebooks, audiobooks, magazines, documents, Scribd Originals and more. In addition to works from major publishers and top authors, our community includes over 1.4M subscribers in nearly every country worldwide.
About the team
Applied Research works on a variety of ML and NLP projects like spam detection, language identification, and text embeddings. We work on Scribd’s unique and massive dataset consisting of hundreds of millions of documents, books, audiobooks, and podcasts. We’re seeking a skilled Senior ML Engineer that specializes in MLOps to help us productionize our wide variety of real time & batch processing models. Our team of 5 data scientists are excited to learn from you about how to efficiently build scalable production systems and to share their knowledge of building high performance machine learning models.
You enjoy teaching the skills you’ve acquired. As a senior ML engineer you’ve developed the ability to deeply understand the larger data ecosystem system from model requirements to business needs. You focus on designing tools and capabilities that help the team deploy more models to production. You’re able to connect what you’re building to the downstream impact of how it will improve the product.
Design and implement ML systems that scale to reach millions of people.
Package tests, build containers, and deploy artifacts in CI/CD pipelines.
Work with our AWS tech stack leveraging S3, ECR, CodeBuild, AWS Lambda, Sagemaker, & Databricks.
Create the interfaces, infrastructure, and clusters to process data efficiently.
Work with other teams improve Scribd’s ML platform: logging, monitoring, scalability, model retraining, automated testing, environment isolation, and model health monitoring.
Build pipelines that process terabytes of data.
Collaborate across teams to determine the highest-impact opportunities.
4+ years of relevant work experience automating ML pipelines and deploying ML models in production environments.
Advanced Spark or Pyspark skills.
Intermediate Python and SQL skills.
Experience optimizing infrastructure usage for performance, reliability, and cost.
An understanding of fundamental ML concepts and exposure to ML libraries like TensorFlow, Pytorch, and Scikit-learn.
Knowledge of relevant software design patterns and system architecture.
Experience working with the AWS technology stack and frameworks and environments such as Airflow and Docker.
Benefits, Perks and Wellbeing at Scribd
• Healthcare Benefits: Scribd pays 100% of employee’s Medical, Vision, and Dental premiums and 70% of dependents
• Leaves: Paid parental leave, 100% company paid short-term/long-term disability plans, and milestone Sabbaticals
• 401k plan through Fidelity, plus company matching with no vesting period
• Diversity, Equity, & Inclusion hiring best practices
• Stock Options - every employee is an owner in Scribd!
• Generous Paid Time Off, Paid Holidays, Flexible Sick Time, Volunteer Day + office closure between Christmas Eve and New Years Day
• Referral bonuses
• Professional development: generous annual budget for our employees to attend conferences, classes, and other events
• Company-wide Diversity, Equity & Inclusion training
• Learning & Development and Coaching programs
• Monthly Wellness, Connectivity & Comfort Benefit
• Concern mental health digital platform
• Work-life balance flexibility
• Employee Resource Groups that build community and support among employees
• Company events + Scribdchats
• Free subscription to Scribd + gift memberships for friends & family
• Monthly inclusive multi-cultural celebrations & learning opportunities
Scribd is committed to equal employment opportunity regardless of race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or any other characteristic protected by law.
We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful.